Shape Servoing of Deformable Objects Using Model Estimation and Barrier Lyapunov Function

An adaptive shape servoing control method is presented in this article to manipulate a deformable object into a desired shape in 3-D. A finite-point-based representation of the deformable object is used and the deformation Jacobian matrix is approximated using Fourier series basis functions. The unk...

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Veröffentlicht in:IEEE/ASME transactions on mechatronics Jg. 29; H. 6; S. 4640 - 4650
Hauptverfasser: Guthikonda, Vrithik Raj, Dani, Ashwin P.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: 2230 Support IEEE 01.12.2024
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Adaptation models
Adaptive control
Algorithms
Barrier Lyapunov function (BLF)-based constrained control
Basis functions
Concurrent computing
Constraint handling
Control methods
Controllers
Deformable models
deformable objects modeling
Deformation
Electronics and Electrical Engineering
Formability
Fourier series
Function analysis
integral concurrent learning (ICL) parameter estimation
Jacobi matrix method
Jacobian matrices
Jacobian matrix
Liapunov functions
Lyapunov methods
Mechanical Engineering
Parameter estimation
Parameters
Robot dynamics
Servocontrol
Servosystems
Shape control
shape servoing
Task analysis
Vectors
ISSN:1083-4435, 1941-014X
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Beschreibung
Zusammenfassung:An adaptive shape servoing control method is presented in this article to manipulate a deformable object into a desired shape in 3-D. A finite-point-based representation of the deformable object is used and the deformation Jacobian matrix is approximated using Fourier series basis functions. The unknown parameters of the deformation Jacobian are learned by using the velocity applied to a control point on the object and corresponding change of positions of the points describing the entire object. An integral concurrent learning (ICL)-based parameter update law is designed along with a constrained controller to satisfy the state constraints on the motion of the control point using Barrier Lyapunov function analysis. ICL-based parameter update law uses data history of velocity and corresponding positions of the points along with their current values. An efficient algorithm to update the history stack using singular value maximization is proposed based on the structure of the regressor matrix. Simulations using a physical simulator and experiments using a robot platform are performed to validate the performance of the proposed controller on two different deformable objects.
Bibliographie:2230 Support
2230
ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1083-4435
1941-014X
DOI:10.1109/TMECH.2024.3382590